"双碳"战略下的数智融合:等离子体反应和分离耦合驱动CO2加氢制甲醇OA
Digital and Intelligent Integration under the"Dual Carbon"Strategy:Plasma Reaction-Separation Coupling for CO2 Hydrogenation to Methanol
传统的热催化CO2转化要求高温高压条件,等离子体能实现常温常压下驱动CO2加氢制甲醇,是节能降碳、实现"双碳"目标的重要举措.本作品设计新型介质阻挡放电(DBD)等离子体液膜反应器,克服高CO2转化率和高甲醇选择性不可兼得的困难,实现了等离子体反应和分离的高效耦合.本实验中针对等离子体反应控温难和工艺参数优化过程复杂两大问题进行数字化设计:利用红外热成像仪对放电区域温度实时监控,克服传统热电偶存在的测量局部性及容易与高压电极尖端放电等缺点,并通过自动控制模块调节冷凝液温度和流速,维持等离子体放电产热与散热的动态平衡,实现精准控温;通过训练人工神经网络(ANN)模型,定量分析复杂工艺参数与反应性能的关系,并确定其影响权重,实现最优条件的智能预测与工艺优化.本专业实验课程融合数字化技术与人工智能方法,通过智能化实验设计培养学生跨学科创新能力,契合新工科人才培养需求.
While conventional thermal catalytic CO2 conversion requires harsh high-temperature and high-pressure conditions,plasma technology enables CO2 hydrogenation to methanol under ambient conditions,representing a crucial approach for energy conservation,carbon reduction,and achieving"double carbon"goals.This study develops an innovative dielectric barrier discharge(DBD)plasma-liquid film reactor that successfully couples plasma reaction with separation technology,overcoming the traditional trade-off between high CO2 conversion and methanol selectivity.Addressing two key challenges in plasma processes—precise temperature control and complex parameter optimization—we implement digital solutions:Infrared thermography provides real-time,comprehensive temperature monitoring of discharge zones,surpassing conventional thermocouples that suffer from localized measurement and interference from high-voltage electrode discharge;An automated control module dynamically adjusts coolant parameters to maintain thermal equilibrium between plasma generation and dissipation.Furthermore,we employ artificial neural network(ANN)modeling for intelligent prediction of optimal conditions and process optimization.This interdisciplinary experiment integrates digital technologies with AI methodologies,fostering students'innovative capabilities in alignment with emerging engineering education requirements.
包至朋;王艺霖;陈愉;贾贝蕊;王从聪;解则安;于学华;赵震
沈阳师范大学化学化工学院,沈阳 110034沈阳师范大学化学化工学院,沈阳 110034沈阳师范大学化学化工学院,沈阳 110034沈阳师范大学化学化工学院,沈阳 110034沈阳师范大学化学化工学院,沈阳 110034沈阳师范大学化学化工学院,沈阳 110034沈阳师范大学化学化工学院,沈阳 110034沈阳师范大学化学化工学院,沈阳 110034
社会科学
红外热成像自动控温人工神经网络反应和分离耦合技术
Infrared thermographyAutomatic temperature controlArtificial neural networkCoupling technology of reaction and separation
《大学化学》 2026 (1)
29-40,12
教育部产学合作协同育人项目(230805940033356)辽宁省研究生教育教学改革研究项目(LNYJG2023280)沈阳师范大学研究生教改项目(YJSJG220240064,YJSJG320240066)沈阳师范大学教育教学改革研究项目(JGYB202482)
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